HearTheSpecies: Using computer audition to understand the drivers of soundscape composition, and to predict parasitation rates based on vocalisations of bird species

HearTheSpecies：使用计算机试听来了解音景构成的驱动因素，并根据鸟类的发声来预测寄生率

• 批准号: 512414116
• 负责人: Professor Dr. Michael Scherer-Lorenzen
• 金额: --
• 依托单位: Abteilung Geobotanik
• 依托单位国家: 德国
• 项目类别: Infrastructure Priority Programmes
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/512414116?language=en
• 关键词: HearTheSpecies; Using; computer; audition; understand

HearTheSpecies is an interdisciplinary project of the Chair of Embedded Intelligence for Health Care and Wellbeing (EIHW) at the University of Augsburg and the Chair of Geobotany at the University of Freiburg (ALU-FR). The intensification of land use is one of the main causes of the current loss of biodiversity. In order to better understand and monitor the links between land use intensity and biodiversity loss, HearTheSpecies aims to harness the potential of a hitherto under-researched data pool: Audio. The impact of land use on the soundscape of a landscape manifests itself in different aspects and scales. Species loss of vocalising animal communities or changes in landscape structure and vegetation density alter the composition of biophony (sounds of wildlife), geophony (sounds of abiotic nature) and anthropophony (sounds caused by humans). On a much finer scale, land use can even affect the vocal characteristics of individual animals by influencing fitness and parasitisation rates. The established land use gradient within biodiversity exploratories provides an excellent research platform to investigate these relationships and thus establish AI-based autonomous acoustic monitoring workflows. Specifically, as part of HearTheSpecies, we aim to develop AI-based automatic diarisation and separation tools that enable coarse separation of biophony, anthropophony and geophony from interwoven soundscape recordings, and fine-grained detection and separation of species and specific abiotic sounds. To do this, we will annotate existing data from previous projects that collected audio recordings within the Biodiversity Exploratories to enable the training of AI algorithms, and collect new audio data in the joint multi-site experiments REX and FOX. In a next step, we will use these separated sounds to model the effects of local and regional land use intensity, landscape configuration and vegetation structure on the composition of the soundscape and individual species of the acoustic community, and predict parasitisation rates in birds based on their song characteristics.

HeartheSpecies是奥格斯堡大学嵌入式卫生保健和福利情报（EIHW）主席的跨学科项目，也是弗莱堡大学（Alu-FR）的地球植物主席。土地利用的强化是当前生物多样性丧失的主要原因之一。为了更好地理解和监视土地使用强度和生物多样性损失之间的联系，炉膛旨在利用迄今为止研究不足的数据库的潜力：音频。土地利用对景观的音景的影响在不同的方面和尺度上表现出来。散发性动物群落的物种丧失或景观结构和植被密度的变化改变了生物的组成（野生动植物的声音），地球生物（异生物的声音）和人类phop诗（人类引起的声音）。在更加细微的范围内，土地利用甚至可以通过影响健身和偏源率来影响单个动物的声音特征。生物多样性探索者中已建立的土地利用梯度为研究这些关系提供了出色的研究平台，从而建立了基于AI的自主声学监测工作流程。具体而言，作为壁炉架的一部分，我们旨在开发基于AI的自动诊断和分离工具，从而使生物循环，拟人噬细胞和地球散发的声音录音，以及细分的检测以及物种的分离以及物种的分离和特定的非生物声音进行大分分离。为此，我们将注释以前项目的现有数据，这些数据收集了生物多样性探索器中的音频记录，以实现AI算法的培训，并在联合多站点实验REX和FOX中收集新的音频数据。下一步，我们将使用这些分离的声音来对局部和区域土地使用强度，景观构型和植被结构对声学和声学群落的单个物种组成的影响进行建模，并根据其歌曲特征来预测鸟类中的寄生率。